Helena Pedro

Proposed, architected, and delivered a secure automated KPI reporting platform with scheduled jobs, enabling managers across 100+ branches to self-serve dashboards and eliminating ~40 hours/week of manual reporting; led a team of 4 cyber-security, data and software engineers during implementation. Diagnosed and resolved month-long intermittent failures in high-value cash-deposits workflows by uncovering hidden SQL lock timeout issues and enhancing database-level logging, restoring transactional reliability across 107 ATMs serving ~1M clients. Designed and implemented high-availability resiliency infrastructures for 2 core microservices of the FX platform, the first being referenced by 8 other microservices, and the second enforcing real-time solvency limits for ~5k high-value trades/day; led 2 junior software engineers in the implementation of both projects. Redesigned and implemented liquidity analytics features by decoupling data ingestion from analytical processing. This accelerated financial availability calculation by 12x.

Architected a high-throughput telemetry pipeline for 200+ construction sites, processing 10k+ daily records; utilized Redis as a write-through cache to ensure sub-second UI responsiveness and 99.9% system availability. Re-engineered a legacy reporting workflow using MongoDB aggregation pipelines to consolidate 7 disparate data streams, reducing execution latency from 2 hours to 1 minute. Restored production performance by diagnosing and eliminating N+1 query patterns and optimizing transaction boundaries; achieved a 30% reduction in peak-time CPU usage and accelerated query speeds by 9x. Hardened the application infrastructure through a strategic NGINX reverse proxy reconfiguration; this security audit was a mandatory prerequisite for securing a high-value corporate partnership.

Built automated ERP-to-database data pipelines to synchronize purchasing and inventory data, eliminating manual reconciliation and reducing operational reporting effort by ~40 hours/week.

Analyzed scientific datasets and built Python-based automation scripts to support data-driven analysis in an industrial environment.

In progress via distance education. Expected completion date: 12/2027